Instructions to use lora-library/egbert-2x-source-bilinear with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lora-library/egbert-2x-source-bilinear with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-2-1-base", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("lora-library/egbert-2x-source-bilinear") prompt = "egbert" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- d4f329ab8fe40c04e083349f62ca5ec84812a8543bfcc1322e1803b5195f4b86
- Size of remote file:
- 3.49 MB
- SHA256:
- 62eeda358d7a684166ec132311e2daa9d32b59475432af595c12c4f828830044
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.